This invention generally relates to image processing, and more specifically to the improvement of image quality of an image using a machine-learned autoencoder.
It is often desirable to send different versions of the same content to different devices. For example, for devices that are limited by available bandwidth, a lower quality version of a content can be provided whereas for devices that are not constrained by available bandwidth, a higher quality version of the content can be transmitted. A user of the device can consume a version of the content that is best suited for the device.
Conventional systems often upsample lower quality content to generate a higher quality content. For example, conventional systems can employ machine learning models to interpolate additional pixels of a lower quality image. The interpolated pixels can be included in the higher resolution image. However, many of these machine learning models generate upsampled images that suffer from deficiencies such as image artifacts that arise due to the upsampling process. In other words, there can be significant differences between a true, higher resolution image and an upsampled image that is predicted from a low resolution image by a trained machine learning model.